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Searx VS NumPy

Compare Searx VS NumPy and see what are their differences

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Searx logo Searx

Open source metasearch engine

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Searx Landing page
    Landing page //
    2021-09-25
  • NumPy Landing page
    Landing page //
    2023-05-13

Searx features and specs

  • Privacy
    Searx does not track your searches or log any user information, safeguarding privacy.
  • Customizable
    The platform allows users to configure their own instances and adjust the settings according to their preferences.
  • Open Source
    Being open-source, Searx encourages transparency and community contributions, improving security and innovation.
  • Multiple Sources
    Searx aggregates results from various search engines and databases, providing a more comprehensive search result.
  • Ad-Free
    Searx does not display ads in its search results, offering a cleaner user experience.

Possible disadvantages of Searx

  • Performance
    Aggregating searches from multiple sources can result in slower performance compared to dedicated search engines.
  • Reliability
    Searx instances can suffer from downtime or availability issues, especially those run by volunteers or smaller providers.
  • Limited Advanced Features
    Searx might not offer some of the advanced features and functionalities available in proprietary search engines like Google.
  • Quality Variability
    Search result quality can vary depending on the sources selected and the instance configuration.
  • User Interface
    The interface may not be as polished or user-friendly as some of the major search engines.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Analysis of Searx

Overall verdict

  • Overall, Searx is considered a good choice for those who prioritize privacy and want unbiased search results. It offers flexibility and transparency, being an open-source platform that can be customized and self-hosted.

Why this product is good

  • Searx is appreciated for being a privacy-focused metasearch engine that aggregates results from multiple search engines without tracking user activity. It advocates for user privacy and provides unbiased search results by not catering to any single engine's algorithm.

Recommended for

  • Users concerned about online privacy and data tracking
  • Individuals looking for an open-source and customizable search engine
  • Those interested in non-biased search results by amalgamating multiple engines
  • Tech-savvy users who may want to self-host their own private search engine

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Searx videos

+ Add

Searx.me: an open source, privacy respecting alternative to Google Search

More videos:

  • Review - DeGoogleing // Duck Duck Go amd Searx
  • Review - TOP 5 privacy search engines - Best Google Search Alternatives - DuckDuckGo, Startpage, Qwant, Searx

NumPy videos

+ Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to Searx and NumPy)

Searx

NumPy

Search Engine
100 100%
Search Engine
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Internet Search
100 100%
Internet Search
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Searx and NumPy. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Searx and NumPy

Searx Reviews

The best private search engines for secure browsing
Searx is a free, privacy-focused metasearch engine. It doesn’t share users’ IP addresses and search history with the search engines it uses. Searx also blocks cookies and protects against tracking HTTPS headers, pixels, and malicious scripts. Moreover, it prevents search result filtering according to your search habits, so it is very handy if you want to minimize third-party...
Source: nordvpn.com
12 Google Alternatives: Best Search Engines To Use In 2019
It retrieves search results from numerous sources that include famous ones like Google, Yahoo, DuckDuckGo, Wikipedia, etc. SearX is an open-source Google alternative and available to everyone for a source code review as well as contributions on GitHub. You can even customize it as your own metasearch engine and host it on your server.
Source: fossbytes.com
8 Privacy Oriented Alternative Search Engines To Google in 2018
If you are fond of utilizing Torrent clients to download stuff, this search engine will help you find the magnet links to the exact files when you try searching for a file through searX. When you access the settings (preferences) for searX, you would find a lot of advanced things to tweak from your end.
Source: itsfoss.com

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy should be more popular than Searx. It has been mentiond 119 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Searx mentions (40)

  • Just a reminder that WhatsApp is also owned by Facebook
    Meaning, you can go to public instances like searx.me,. Here's the documentation on how to start it up. But , you dont have to trust Searx that they are good people nor do you have to trust their data habits like DDG. Source: about 3 years ago
  • Instead of lashing out at duckduckgo for doing what they think is best, ask the deeper question of why we’re all still using centralized services and being disappointed when they behave in a predictably centralized way.
    Consider a future where something like https://searx.me/ is as ubiquitous as Tor. Source: over 3 years ago
  • DDG, once a hero has now fallen.
    For those looking for a replacement for Duckduckgo; I would highly recommend using Searx. It's an open source privacy respecting search engine with many decentralized private instances you can swap between. The link I sent is the primary instance, but here is a link with dozens more, and my own private instance. Source: over 3 years ago
  • DuckDuckGo is out. I guess I'll try Brave Search.
    The most based solution: Https://searx.me. Source: over 3 years ago
  • Uh oh.. What will the vaccinated think of this news?
    Searx.me and Startpage.com are the best search engines right now that are anti-censorship and anti-bias. Source: over 3 years ago
View more

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 8 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 10 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
View more

What are some alternatives?

When comparing Searx and NumPy, you can also consider the following products

DuckDuckGo - The Internet privacy company that empowers you to seamlessly take control of your personal information online, without any tradeoffs.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Google - Google Search, also referred to as Google Web Search or simply Google, is a web search engine developed by Google. It is the most used search engine on the World Wide Web

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

StartPage - Startpage search engine, the new private way to search Google. Protect your Privacy with Startpage!

OpenCV - OpenCV is the world's biggest computer vision library

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